Agent-environment interface describes the interaction between agent and environment in reinforcement learning. The boundary between agent and environment is preset according to task. "The agent-environment
boundary is determined once one has selected particular states, actions, and rewards, and thus has identified a specific decision-making task of interest" [1]}. However, agent-environment interface is of little interest of algorithm development since it is related to the task definition itself more than how to solve the task.
